Machine Learning Operations Engineer

Proactive Appointments; Greater London; Hybrid; GBP 150,000 - 200,000; Full time

Job summary

A leading financial services firm based in London is seeking a Machine Learning Operations Engineer to manage and enhance machine learning models. The role involves designing, deploying, and optimizing models using Azure ML, as well as collaborating closely with actuarial teams. The ideal candidate will have significant experience in machine learning operations and data management, along with strong communication skills. This position offers a competitive salary and a flexible work environment.

Benefits

Competitive salary

Discretionary Bonus Scheme

Pension Plan

Life Assurance cover

Employee assistance programme

25 days holiday

Access to a qualified GP 24/7

Qualifications

• Experience designing and deploying business-critical machine learning models using Azure ML.
• Proficient in data wrangling using Python, SQL and ADF.
• Strong communication skills to convey technical concepts to non-technical stakeholders.

Responsibilities

• Collaborate with actuarial analysts to develop machine learning models for pension schemes.
• Design, deploy, and maintain machine learning models using Azure ML.
• Collect and preprocess large datasets for analysis.

Skills

Azure ML

Python

SQL

CI/CD practices

Data visualization

Job description

Machine Learning Operations Engineer

Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London.

To be considered for the role you must have the following essential skills & experience:

Key Skills & Experience

• Model development: Work collaboratively with actuarial analysts to develop machine learning and statistical models to predict outcomes, related to pension schemes, such as life expectancy, default risk, or investment returns. Identify appropriate machine learning algorithms and apply them to enhance predictions, automate decision-making processes, and improve client offerings.
• Machine Learning Operations: Responsible for designing, deploying, maintaining and refining statistical and machine learning models using Azure ML. Optimize model performance and computational efficiency. Ensure that applications run smoothly and handle large-scare data efficiently. Implement and maintain monitoring of model drifts, data-quality alerts, scheduled r-training pipelines.
• Data Management and Preprocessing: Collect, clean and preprocess large datasets to facilitate analysis and model training. Implement data pipelines and ETL processes to ensure data availability and quality.
• Software Development: Write clean, efficient and scalable code in Python. Utilize CI/CD practices for version control, testing and code review.
• Work closely with actuarial analysts, actuarial modelling team (AMT) and other colleagues in the company to integrate data science findings into practical advice and strategies.
• Stay abreast of new trends and technologies in Data Science technologies and pensions to identify opportunities for innovation.
• Provide training and support to other team members on using machine learning tools and understanding analytical techniques.
• Interpret and explain machine learning concepts and findings to other members of the analytics team and non-technical stakeholders within the company.

Technical Skills required

• Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments.
• Experience in data wrangling using Python, SQL and ADF.
• Experience in CI/CD and DevOps/MLOps and version control.
• Familiarity with data visualization and reporting tools, ideally PowerBI.
• Good written and verbal communication and interpersonal skills.
• Ability to convey technical concepts to non-technical stakeholders.
• Experience in the pensions or similar regulated financial services industry is highly desirable.
• Experience in working within a multidisciplinary team would be beneficial

Benefits

• We offer an attractive reward package; typical benefits can include:
• Competitive salary
• Participation in Discretionary Bonus Scheme
• A set of core benefits including Pension Plan, Life Assurance cover and employee assistance programme, 25 days holiday and access to a qualified, practising GP 24 hours a day/365 days a year
• Flexible Benefits Scheme to support you in and out of work, helping you look after you and your family covering Security & Protection, Health & Wellbeing, Lifestyle

Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted.

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